Tldr Deep

作者 parcadeid07ff4b06b62無授權條款3.9K 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫8 個月前更新

Full 5-layer analysis of a specific function. Use when debugging or deeply understanding code.

僅含說明Software Development

AI 產生的概覽

使用 tldr 命令列工具對單一函式進行五層靜態分析，協助除錯與理解程式碼。

功能: 此技能引導代理對單一函式執行五層分析：AST 結構、呼叫圖、控制流程圖、資料流程圖與程式切片。它列出每一層對應的 tldr 指令，並規定結構化輸出格式，涵蓋函式簽章、呼叫與被呼叫關係、循環複雜度、變數定義與使用，以及切片相依性。文件也說明以程式方式執行這些層級的 Python API。
適用情境: 適用於除錯複雜函式、重構時了解相依關係、審查複雜函式，以及透過循環複雜度找出效能熱點。
執行需求: 需要安裝並可使用 tldr 命令列工具及其 Python API（tldr.api）；此技能本身不附帶指令碼，僅提供指示。

TLDR Deep Analysis

Full 5-layer analysis of a specific function. Use when debugging or deeply understanding code.

Trigger

/tldr-deep <function_name>
"analyze function X in detail"
"I need to deeply understand how Y works"
Debugging complex functions

Layers

Layer	Purpose	Command
L1: AST	Structure	`tldr extract <file>`
L2: Call Graph	Navigation	`tldr context <func> --depth 2`
L3: CFG	Complexity	`tldr cfg <file> <func>`
L4: DFG	Data flow	`tldr dfg <file> <func>`
L5: Slice	Dependencies	`tldr slice <file> <func> <line>`

Execution

Given a function name, run all layers:

bash

# First find the filetldr search "def <function_name>" .
# Then run each layertldr extract <found_file>              # L1: Full file structuretldr context <function_name> --project . --depth 2  # L2: Call graphtldr cfg <found_file> <function_name>  # L3: Control flowtldr dfg <found_file> <function_name>  # L4: Data flowtldr slice <found_file> <function_name> <target_line>  # L5: Slice

# First find the filetldr search "def <function_name>" .
# Then run each layertldr extract <found_file>              # L1: Full file structuretldr context <function_name> --project . --depth 2  # L2: Call graphtldr cfg <found_file> <function_name>  # L3: Control flowtldr dfg <found_file> <function_name>  # L4: Data flowtldr slice <found_file> <function_name> <target_line>  # L5: Slice

Output Format

## Deep Analysis: {function_name}
### L1: Structure (AST)File: {file_path}Signature: {signature}Docstring: {docstring}
### L2: Call GraphCalls: {list of functions this calls}Called by: {list of functions that call this}
### L3: Control Flow (CFG)Blocks: {N}Cyclomatic Complexity: {M}[Hot if M > 10]Branches:  - if: line X  - for: line Y  - ...
### L4: Data Flow (DFG)Variables defined:  - {var1} @ line X  - {var2} @ line YVariables used:  - {var1} @ lines [A, B, C]  - {var2} @ lines [D, E]
### L5: Program Slice (affecting line {target})Lines in slice: {N}Key dependencies:  - line X → line Y (data)  - line A → line B (control)
---Total: ~{tokens} tokens (95% savings vs raw file)

## Deep Analysis: {function_name}
### L1: Structure (AST)File: {file_path}Signature: {signature}Docstring: {docstring}
### L2: Call GraphCalls: {list of functions this calls}Called by: {list of functions that call this}
### L3: Control Flow (CFG)Blocks: {N}Cyclomatic Complexity: {M}[Hot if M > 10]Branches:  - if: line X  - for: line Y  - ...
### L4: Data Flow (DFG)Variables defined:  - {var1} @ line X  - {var2} @ line YVariables used:  - {var1} @ lines [A, B, C]  - {var2} @ lines [D, E]
### L5: Program Slice (affecting line {target})Lines in slice: {N}Key dependencies:  - line X → line Y (data)  - line A → line B (control)
---Total: ~{tokens} tokens (95% savings vs raw file)

When to Use

Debugging - Need to understand all paths through a function
Refactoring - Need to know what depends on what
Code review - Analyzing complex functions
Performance - Finding hot spots (high cyclomatic complexity)

Programmatic API

python

from tldr.api import (    extract_file,    get_relevant_context,    get_cfg_context,    get_dfg_context,    get_slice)
# All layers for one functionfile_info = extract_file("src/processor.py")context = get_relevant_context("src/", "process_data", depth=2)cfg = get_cfg_context("src/processor.py", "process_data")dfg = get_dfg_context("src/processor.py", "process_data")slice_lines = get_slice("src/processor.py", "process_data", target_line=42)

from tldr.api import (    extract_file,    get_relevant_context,    get_cfg_context,    get_dfg_context,    get_slice)
# All layers for one functionfile_info = extract_file("src/processor.py")context = get_relevant_context("src/", "process_data", depth=2)cfg = get_cfg_context("src/processor.py", "process_data")dfg = get_dfg_context("src/processor.py", "process_data")slice_lines = get_slice("src/processor.py", "process_data", target_line=42)

來源與署名

來源：parcadei/continuous-claude-v3位於.claude/skills/tldr-deep提交d07ff4b

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檢舉或申請下架

Tldr Deep

TLDR Deep Analysis

Trigger

Layers

Execution

Output Format

When to Use

Programmatic API

來源與署名

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